Developers and ML engineers face a variety of challenges when it comes to operationalizing Spark ML workloads. One set of challenges may come in the form of infrastructure concerns, for example, how to provision infrastructure clusters in advance, how to ensure that there are enough resources to run different kinds of tasks like data preparation, […]

Without a central place to manage models, those responsible for operationalizing ML models have no way of knowing the overall status of trained models and data. This lack of manageability can impact the review and release process of models into production, which often requires offline reviews with many stakeholders.  Earlier this week we announced Vertex […]

At Google Cloud, we believe that democratizing access to fresh, consistent, enterprise data is the key to driving digital and cultural transformation. This means empowering everyone to leverage rich, governed data sets and harness the power of data — without learning new tools or building specialized skills. This is why we are excited to provide […]

At Mercado Libre, we are obsessed with unlocking the power and potential of data. One of our key cultural principles is to have a Beta Mindset. This means that we operate in a “state of beta”, constantly asking new questions of our data, experimenting with technologies and iterating our business operations in service of creating […]

Today, a typical enterprise uses over 100 SaaS applications while large organizations  commonly use over 400 apps. These applications contain valuable data on customers, suppliers, employees, products and more, offering the potential for valuable insights and powerful workflows. However, in the past, this data has often remained siloed and underutilized, even within an application.  Customer […]